Lithography Source Mask Target Optimization
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Solution Overview
Problem
Conventional lithographic optimization methods, such as optical proximity correction, separate the lithographic transfer process and circuit device physics, leading to limited design improvements and segregation of direct design considerations from automated mask data preparation, resulting in suboptimal target shape design and process yield.
Innovation Solution
A method and system for simultaneously determining source, mask, and target shapes in lithography processes by formulating optimization problems that incorporate contour-based assessments and process variation integrations, allowing for the simultaneous optimization of source, mask, and target shapes with constraints such as tolerance bands and process window constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional lithographic optimization methods are used, then the process is simpler and easier to operate, but the manufacturing precision and yield are limited
Solution Approach 1:
The patent merges the lithographic transfer process optimization with circuit device physics optimization into a single integrated framework. The contour-based assessment combines printability constraints with circuit functionality requirements, allowing simultaneous optimization of source, mask, and target shapes while considering both lithographic process variations and circuit performance implications.
Solution Approach 2:
The patent introduces contour-based assessments that evaluate target shapes based on multiple parameters including tolerance bands, process window constraints, and circuit functionality. The optimization process varies multiple parameters simultaneously (source shape, mask shape, target shape) rather than adjusting them separately, enabling precise control over manufacturing outcomes.
2Productivity
If manual retargeting is performed, then the design process is more flexible, but the productivity and time required increase
Solution Approach 1:
The patent implements automated optimization that self-adjusts source, mask, and target shapes based on contour-based assessments and process variation integration. The system automatically evaluates printability constraints and circuit functionality requirements, eliminating the need for manual iterative retargeting while maintaining design flexibility.
Solution Approach 2:
The patent incorporates feedback mechanisms where contour-based assessments continuously evaluate target shape quality against tolerance bands and process constraints. This feedback loop enables automated adjustments to source and mask shapes to achieve optimal target shapes, reducing manual intervention and iterative design cycles.
3Reliability
If separate frameworks are used for lithography and circuit design, then the ease of operation is maintained, but the manufacturing precision and overall functionality are reduced
Solution Approach 1:
The patent combines lithographic transfer process optimization with circuit device physics into a unified framework. The contour-based assessment integrates printability constraints with circuit functionality requirements, allowing simultaneous optimization of both aspects while considering their interdependencies and improving overall process yield.
Solution Approach 2:
The patent creates a universal optimization framework that handles multiple functions simultaneously: lithographic process optimization, circuit functionality assessment, and yield maximization. The contour-based assessment serves multiple purposes including printability verification, tolerance band compliance checking, and circuit design validation within a single integrated process.
Data Source
AI summary
Methods and systems for determining a source shape, a mask shape and a target shape for a lithography process are disclosed. One such method includes receiving source, mask and target constraints and formulating an optimization problem that is based on the source, mask and target constraints and incorporates contour-based assessments for the target shape that are based on physical design quality of a circuit. Further, the optimization problem is solved by integrating over process condition variations to simultaneously determine the source shape, the mask shape and the target shape. In addition, the determined source shape and mask shape are output.